The present invention relates to medical imaging and more particularly to a method and an apparatus for compressing imaging data to expedite data transfer, storage and retrieval and minimize required storage space.
As an initial matter, while the present compression method and apparatus could be used with any of several different imaging modalities (e.g. PET, CT, etc.), in order to simplify this explanation the invention will be described in the context of a PET system. However, the invention should not be so limited.
Positrons are positively charged electrons which are emitted by radio nuclides that have been prepared using a cyclotron or other device. The radio nuclides most often employed in diagnostic imaging are fluorine-18 (.sup.18 F), carbon-11 (.sup.11 C), nitrogen-13 (.sup.13 N), and oxygen-15 (.sup.15 O). Radio nuclides are employed as radioactive tracers called "radiopharmaceuticals" by incorporating them into substances such as glucose or carbon dioxide. One common use for radiopharmaceuticals is in the medical imaging field.
To use a radiopharmaceutical in imaging, the radiopharmaceutical is injected into a patient and accumulates in an organ, vessel or the like, which is to be imaged. It is known that specific radiopharmaceuticals become concentrated within certain organs or, in the case of a vessel, that specific radiopharmaceuticals will not be absorbed by a vessel wall. The process of concentrating often involves processes such as glucose metabolism, fatty acid metabolism and protein synthesis. Hereinafter, in the interest of simplifying this explanation, an organ to be imaged will be referred to generally as an "organ of interest" and prior art and the invention will be described with respect to a hypothetical organ of interest.
After the radiopharmaceutical becomes concentrated within an organ of interest and while the radio nuclides decay, the radio nuclides emit positrons. The positrons travel a very short distance before they encounter an electron and, when the positron encounters an electron, the positron is annihilated and converted into two photons, or gamma rays. This annihilation event is characterized by two features which are pertinent to medical imaging and particularly to medical imaging using photon emission tomography (PET). First, each gamma ray has an energy of essentially 511 keV upon annihilation. Second, the two gamma rays are directed in substantially opposite directions.
In PET imaging, if the general locations of annihilations can be identified in three dimensions, a three dimensional image of an organ of interest can be reconstructed for observation. To detect annihilation locations, a PET camera is employed. An exemplary PET camera includes a plurality of detector units and a processor which, among other things, includes coincidence detection circuitry. An exemplary detector unit includes a 6.times.6 matrix of bismuth germinate (BGO) scintillator crystals which are disposed in front of four photo multiplier tubes (PMTs). When a crystal absorbs a photon, the crystal generates light which is generally directed toward the PMTs. The PMTs absorb the light and each PMT produces an analog signal which arises sharply when a scintillation event occurs and then tails off exponentially with a time constant of approximately 300 nanoseconds. The relative magnitudes of the analog PMT signals are determined by the position in the 6.times.6 BGO matrix of the crystal which generates the light (i.e. where the scintillation event takes place), and the total magnitude of these signals is determined by the energy of the photon which caused an event.
A set of acquisition circuits receives the PMT signals and determines x and y event coordinates within the BGO matrix thereby determining the crystal which absorbed the photon. Each acquisition circuit also produces an event detection pulse (EDP) which indicates the exact moment at which a scintillation event took place.
The information regarding each valid event is assembled into a digital event data packet which indicates precisely when the event took place and the position of the BGO crystal which detected the event. Event data packets are conveyed to a coincidence detector which determines if any two events are in coincidence. Coincidence is determined by a number of factors. First, the time markers in each event data packet must be within a specific time window of each other, and second, the locations indicated by the two event data packets must lie on a straight line which passes through the field of view of a scanner imaging area. Events which cannot be paired as coincidence events are discarded, but coincidence event pairs are located and recorded as a coincidence data packets (CDPs). Each coincidence data packet includes a pair of digital numbers which precisely identify the addresses of the two BGO crystals that detected the event.
To compress annihilation data somewhat, instead of separately storing an indication of each CDP, a typical PET processor simply stores a separate counter for each possible "meaningful" detector pair. What is meant by the term "meaningful" is that there are certain theoretically possible detector pairs which will almost certainly never provide a true annihilation indication. For example, because an annihilation typically sends gamma rays in opposite directions and annihilation points are within an imaging area, it is essentially impossible for two adjacent detectors to provide a true annihilation indication. Similarly, other detectors which are disposed in the same general area as a first detector cannot provide a true annihilation indication along with the first detector. Thus, proximate detectors are not meaningful pairs and the processor does not provide a counter for these pairs.
In addition, the number of meaningful detector pairs is also limited by the fact that certain detector pairs are positioned such that the organ of interest, and any radiopharmaceutical accumulated therein, is not within the space there between. In this case, once again, the detector pair cannot provide a true annihilation indication. Thus, while theoretically it is possible to have approximately 144 million detector pairs where there are 12,000 crystals, instead of providing 144 million counters and memory required to store 144 million annihilation counts, the meaningful number of detector pairs and hence processor counters, is reduced to approximately 25 million.
After an acquisition period coincidence counts are transferred to secondary memory storage devices during an archiving process. Thereafter the system can be used to acquire data corresponding to another image. The archived data is then used by image construction software which employs any of several different back projection techniques which are well known in the industry to generate a three dimensional image of the organ of interest which is viewable via an electronic display. While PET systems as described above facilitate high quality image generation, the amount of data required to generate a PET image leads to some practical problems which increase system costs and reduce system efficiency. First, a typical PET counter is 16 bit so that large numbers of coincidence events can be detected and tallied. This means that, even where the number of counters is minimized by selecting only meaningful coincidence pairs, the amount of raw data produced during a single three-dimensional scanning period is approximately 500 Megabytes. To store 500 Megabytes of data during an acquisition period large on line and dedicated storage devices are required.
Because such massive on line memory is required for each PET image generated, most on line memory systems cannot accommodate more than a single set of PET image data at one time. Therefore, in between PET acquisition periods PET data has to be archived on the secondary memory devices. Data acquisition cannot be performed during archiving and therefore archiving reduces PET system efficiency.
This archiving problem is exacerbated by the fact that archiving is an extremely time consuming process. To reduce overall costs secondary data storage devices used to store PET data are typically configured using inexpensive hardware which can only receive data at relatively slow speeds. For example, an exemplary secondary storage device uses Advance DAT tape as the storage medium which can only receive data at approximately 150 Kb per second. Thus, the archiving process to archive 500 Megabytes of data takes a long time. 20 Second, just as massive on line memory is required to acquire PET data, massive secondary memory is also required which increases system costs.
Third, just as typical secondary memory is only capable of receiving data at a relatively slow speed, during subsequent data retrieval, data can only be accessed at a slow speed (e.g. 150 kb/sec) due to hardware constraints.
One way to reduce the amount of secondary memory required to support a PET system is to use PET data only once to generate a PET image data set via back projection techniques and then store the image data set, discarding the raw PET data.
Unfortunately, in most cases it is advantageous to save PET raw data. This is because the PET industry is constantly developing new and improved back projection techniques which result in better PET images from raw PET data. Where raw data is discarded new raw data has to be generated to provide an image, this process being time consuming and expensive.
Another solution to speed up data transfer to secondary memory, speed up data retrieval from secondary memory and reduce the size of the secondary memory required to store PET data is to compress PET data into a reduced data set. Many different data compression schemes have been used to compress raw data. An exemplary and well known data compression scheme which has been used in the PET imaging area is referred to as the Lempel-Ziv (LZ) compression algorithm. The LZ algorithm successfully reduces raw data size and can be used to subsequently expand compressed data.
Unfortunately, the LZ algorithm was developed as a general data compression scheme for use in many different industries. Because of its many different uses the LZ algorithm accounts for many different factors and therefore is computationally extremely intensive. Thus, to implement the LZ algorithm using a PET scanner a relatively large amount of time is required to compress and/or expand raw data. While the LZ and other similar compression schemes reduce the overall time required for data transfer from a PET system and data retrieval from a secondary storage device, the time required for such transactions is still appreciable. In this regard, the LZ method is exemplary of other compression schemes which require excessive time to compress data.